Title :
Bernoulli Forward-Backward Smoothing for Track-Before-Detect
Author :
Shanhung Wong ; Ba Tuong Vo ; Papi, Francesco
Author_Institution :
Dept. of Electr. & Comput. Eng., Curtin Univ., Bentley, WA, Australia
Abstract :
Track-before-detect (TBD) refers to an alternative approach to tracking which utilizes the full sensor information rather than detections obtained from thresholding. In this letter we investigate whether forward-backward smoothing for TBD can increase performance. We propose a novel algorithm based on the random finite set framework which incorporates the TBD sensor model with multi-scan information. The algorithm is tested on a typical scenario which confirms improved tracking.
Keywords :
Bayes methods; random processes; set theory; signal detection; smoothing methods; tracking filters; Bernoulli filter; Bernoulli forward-backward smoothing; TBD sensor model; full sensor information; multiscan information; random finite set framework; recursive Bayesian approach; track-before-detect; tracking filter; Bayes methods; Density measurement; Proposals; Signal processing algorithms; Signal to noise ratio; Smoothing methods; Time measurement; Random finite set; smoothing; track-before- detect;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2014.2310137
